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Instability of a Gold Mine Tailings Subjected to Different Stress Paths

2022· article· en· W4214516363 on OpenAlexaff
Amir reza Fotovvat, Abouzar Sadrekarimi

Bibliographic record

VenueJournal of Geotechnical and Geoenvironmental Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsWestern University
Fundersnot available
KeywordsTailingsGeotechnical engineeringConsolidation (business)Shearing (physics)Stress pathLiquefactionGeologyShear (geology)Materials scienceMetallurgyPetrology

Abstract

fetched live from OpenAlex

Static liquefaction of mine tailings has been the interest of many studies as these materials are generally deposited in a loose condition and stored at high saturation ratios. Yet few researchers have investigated the behavior of mine tailings in stress paths involving extensional consolidation or shearing in extension. In this study, the results of a set of experiments aimed at investigating the static liquefaction behavior of saturated loose gold mine tailings samples in triaxial compression and extension shear tests are described. Monotonic tests are carried out on isotropically and K0-consolidated samples to assess the effect of stress-induced anisotropy and mode of shearing on the instability and critical state behaviors of tailings. The comparison of undrained extension and compression shearing behaviors of samples consolidated to similar densities and stress conditions show a profound difference in their undrained shearing responses. This is attributed to the angular shapes of tailings particles that amplify the effects of particle orientation and sample fabric, as well as microstructural changes induced by different loading paths. Postliquefaction and yielding undrained shear strengths and effective friction angles from different modes of consolidation and shearing are examined. In both undrained compression and extension tests, tailings samples exhibit a limited liquefaction behavior after yielding, followed by a strain-hardening (dilative) behavior. Differences in tailings behavior under different loading directions and anisotropic stresses indicate the importance of considering the effects of these phenomena on the stability analysis of mine tailings dams.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.940

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.157
Teacher spread0.154 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations26
Published2022
Admission routes1
Has abstractyes

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